Multivariate time series Vector Autoregression Model (VAR) on real world GDP and DPI (and some other indexes). Bayesian Structured Time Series (BSTS).

Crop yield Forecasting on the basis of meteorological predictions using some Time series & ML models

This repo contains files for the blog post about conjoint analysis

A comprehensive implementation of various Regression Techniques in Machine Learning.

Forecast the Airlines Passengers and CocaCola Prices data set. Prepare a document for model explaining. How many dummy variables you have created and RMSE value for model. Finally which model you will use for Forecasting.

Orange3 widgets wrapping Statmodels library

Using Python to work up a Design of Experiments

My this project repository focused on hypothesis testing involving T-test, Chi-square test, Binomial Test, ANOVA, Sample Size Determination with scipy, statmodels modules.

Tutorials for BSE classes.

Used libraries and functions as follows:

ExcelR Data Science Assignment No 3

Influence of 17-AAG a Hsp90 inhibitor on signaling pathway in Atopic Dermatitis

Анализ соответствия размера выборки и плановых значений метрик A/B-теста

Created model using Linear regression to predict variables impacting demand.

Predict delivery time using sorting time and Build a prediction model for salary hike.

Project analyzes the price trends, correlations, and patterns of Bitcoin, Ethereum, and Binance Coin (2020–2024) using Python and statistical methods. It explores volatility, trends, seasonality, and forecasts future prices while assessing interdependencies and stability during major economic events.

Apprentissage supervisé : Création de modèles prédictifs

Prepare a prediction model for profit of 50 startups data and Consider only the some columns and prepare a prediction model for predicting Price.

업무프로세스 개선을 위한 관리자의 의사결정 프로그램(현대중공업 DT 프로젝트)

Autoregressive (AR) models with advanced techniques: model selection, diagnostics, structural breaks, rolling forecasts, Fourier seasonality, exogenous variables, business cycle analysis, and benchmarking for economic time series.

Tried to understand whether the company should implement a new page or keep the old page with some statistical techniques.

ExcelR Data Science Assignment No 2

Model created using Logistic Regression to identify potential leads

Time Series forecasting using Seasonal ARIMA. Applied statistical tests like Augmented Dickey–Fuller test to check stationary of series. Checked ACF ,PACF plots. Transformed series to make it stationary

A comprehensive explanation of Generalized Linear Models (GLMs) with Python examples, covering Binomial, Gamma, and Gaussian families, model diagnostics, formula interface, and alternative estimation approaches using statsmodels.

ExcelR Data Science Assignment No 1

Causal analysis of U.S. air pollution data (2000-2016) using Granger causality tests and OLS regression. EPA data across all states, ADF stationarity testing, statsmodels. Finds NO2 and CO causally precede ozone formation. UT Dallas graduate project.

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Explorer, nettoyer et analyser pour effectuer une modélisation des données

Exploration of descriptive and inferential statistical methods using Python and Jupyter Notebook.